Visual Encoder  
The visual encoder represents the image with a set of region-based visual feature vectors \(V=\left\lbrace v_{1}, v_{2}, \ldots , v_{N}\right\rbrace  \in \mathbb {R}^{d \times N}\) , where each feature vector represents a certain aspect of the image.
The visual features serve as a guide for the language decoder to describe the salient information in the image.
In implementation, the Faster-RCNN model [1]}, [2]} is widely adopted as the region-based visual feature extractor, which has achieved great success in advancing the state-of-the arts [3]}, [4]}, [5]}, [6]}.
